r/malcolmrey

a womand stands on a grand crystal staircase, looking back over her shoulder toward camera in a three-quarter rear pose, wearing a floor-length deep crimson sequined halter gown with a daring open back, diamond-embellished cutout at the hip, and a high front slit revealing strappy crystal stilettos, accessorized with a sparkling diamond choker necklace, matching chandelier earrings, and a wide crystal cuff bracelet on her left wrist, her dark hair swept up into a loose updo with soft face-framing tendrils, wearing bold red lip color, set against a sweeping curved grand staircase with crystal-encrusted steps and ornate gold balustrade draped with cascading crystal pendants, a glittering chandelier visible overhead in a warm opulent ballroom interior, lit with warm golden ambient light from crystal chandeliers supplemented by soft frontal fill light creating gentle specular highlights across the sequin fabric and diamond accessories, subsurface scattering visible on bare skin at the back and décolletage, natural skin pores and high-frequency skin texture rendered with photorealistic clarity, shot on an 85mm lens at f/1.8 aperture, shallow depth of field with the staircase background rendered in a soft bokeh of silver and gold light points, full-body editorial fashion photography, ultra-high resolution

Helo, guys.

I've made this workflow where I can input any image and it will make a similar image using a character LORA.

It's made for ZIT since it's fast but it can be used for any model, just modify it.

It takes less than a minute at second run at this resolution on my RTX 4070 Super (12GB VRAM) and 64GB RAM.

&gt; VAE and CLIP loader nodes under the Load image Node. <Load your ZIT VAE and CLIP properly

Link: https://pastebin.com/pGXEhDc8
(Updated: Removed the WAS Node Pack, no need for it. VAE and CLIP changed to the default ZIT ones)

It works in 3 Steps:

1- The image is downscaled to 768 on longer edge, Qwen3VL creates a basic prompt for it. Play with Denoise value here to best suit your preferences, around 0.45 - 0.55 seems ok for me.

2- Latent Upscale of 2x. I have best results like this, even with T2I.
The image will look better and the character LORA will be used again.

3- Face fix pass. The face will be detected with SAM3 and again refined with the LORA using the Inpaint Crop node. A small amount of sharpness is applied in this step.

Theres a group bypasser node so you can enable/disable steps 2 and 3. The image is only saved on step 3.

For the prompt, I'm suing a text concatenate so I can have my LORA trigger word and any other prompt applied before the Qwen3VL prompt.

Hope it's useful for someone o/

Total noob question here, so please bear with me.
I’m trying to understand how to train a LoRA on custom models inside Ostris AI Toolkit GitHub, but I’m clearly missing something important.
From what I understand:
we need to change the model path to the custom model folder,
and I vaguely remember the model needing to be a .gguf file (not even sure if that’s correct :).
But in practical use, my training fails every single time.
Could someone explain in simple beginner-friendly words:
what exact model format is needed,
where the custom model should be placed,
how the path should be configured,
and what additional settings are required for custom architectures/models?
If anyone has:
a proper tutorial,
documentation,
or especially a good YouTube video covering this exact topic,
please share it.

A young woman in her late twenties with natural, ash-blonde hair tucked loosely behind one ear. She has clear skin with subtle, faint freckles across the bridge of her nose and cheekbones. She is sitting near a window, head turned slightly to look past the camera with a small, genuine, half-smile. The setting is a sun-drenched, minimalist room with white walls and a sheer linen curtain partially pulled to the side. Early afternoon sunlight spills through the fabric, creating a soft, diffused glow that wraps gently around her facial features. The light catches the moisture in her eyes and defines the individual fine hairs around her hairline and the texture of her cream-colored wool sweater. Shadows are soft and filled with ambient bounce from the light walls.

STYLE ANNOTATION:

Style: Intimate editorial portrait photography. Shot on 85mm f/1.8 lens, shallow depth of field, sharp focus on the eyes with a creamy bokeh background. Film stock emulation: Kodak Portra 400 for natural skin tones and soft grain. Mood: Quiet, contemplative, serene.

So I made the following post: https://www.reddit.com/r/malcolmrey/comments/1t6fr4a/training_my_first_lora/

A day later, today, I was able to finally complete the LoRA after many restarts and changes. I think I got a good result and I'm quite happy with the likeness considering my expectations were quite low, although, I do believe I still could have done a lot of things better especially after I changed learning rate and timestamp_type mid training which I think definitely dropped the likeness I would have approached had I kept going with things unchanged. I wanted to share the LoRA, but unfortunately, in adittion to the mess ups i made during training I also messed up a lot of things in regards to captioning.

As it is my first completed LoRA, I was unaware of the nuances of captions and the drawbacks of captioning literally every aspect of the subject. I unfortunately rendered the LoRA so highly dependent on captions that another user probably won't be able to generate a good image without knowing my dataset.

I will be redoing this LoRA and fixing that, and certainly after that, I will be sharing the LoRA as well. I hope some of you will look forward to that.

Also, I hope someone can guide me regarding the best strategy in regards to learning rate and timestamp type.

For this LoRA, I switched between different learning rates and timestamp types and I think I messed some things up. I still want to experiment with that for the finer details and the late-step polishing, and some tips would make that a whole lot easier.

BTW no upscaling or post on these sample photos. Also eulerflowdiscrete scheduler brings out exceptionally realistic details I was aiming for, I will share the sample of that later.